class_docstr: Small wrapper for one simple one machine.
code: def __init__(self, data, spec):
      self._data = data
  
      if isinstance(spec, str):
          self._spec = phoenix_spec_pb2.PhoenixSpec()
          with tf.io.gfile.GFile(spec, "r") as f:
              text_format.Parse(f.read(), self._spec)
      else:
          self._spec = spec
  
      self._tuner_id = "tuner-1"
  
file_path: model_search/model_search/single_trainer.py
imports: import keras_tuner
  from model_search import oss_trainer_lib
  from model_search import phoenix
  from model_search.proto import phoenix_spec_pb2
  import tensorflow.compat.v2
  from google.protobuf import text_format
label_desc: Use image node_id 1 to create a new SingleTrainer object from inherited base classes: object with example: obj = SingleTrainer(data, spec)